Marine Controlled Source Electromagnetic (CSEM) methods have recently received increased attention as a hydrocarbon exploration tool; see for example MacGregor and Sinha (2000), Eidesmo et al.(2002) and Johansen et al (2005). The interest has resulted from the technique's ability to directly detect the presence of thin hydrocarbon bearing layers. Initially, the data were analyzed by plotting the electric field amplitude versus source-receiver offset, and then by normalizing the data that were acquired over a possible hydrocarbon prospect by data measured over a similar non-hydrocarbon bearing area (Eidesmo et al., 2002). Because the presence of hydrocarbon increases the amplitude of the measured electric field, the normalized value will be greater than unity for areas containing resistive anomalies, and unity or less for non-hydrocarbon bearing zones. Although this method will provide information on the presence of hydrocarbon, as well as some information about the horizontal location and extent of the reservoir, it is difficult to discern its depth and its true geometry.
Another method requires making an assumption regarding the location and geometry of the reservoir. This assumption incorporates a risk that if the assumption is wrong that it will create a bias in the result such as some of the time indicating the absence of hydrocarbons when hydrocarbons are actually present and some of the time indicating that hydrocarbons are present when they are actually absent. This bias can be eliminated by employing an inversion approach as characterized in the present application.
To provide this additional information, one will need to employ an inversion approach. For producing approximate images of subsurface conductivity structure, one can employ fast imaging techniques such as the migration wave-field imaging approaches, e.g. Tompkins (2004) and Mittet, et al. (2005). These approaches generally provide low-resolution images that can be difficult to interpret in terms of true conductivity structure. Other approaches involve rigorous inversion algorithms such as the schemes employed in Newman and Alumbaugh (1997) and MacGregor and Sinha (2000). This tends to be computationally expensive due to the employed forward modeling schemes that rely on iterative matrix solution techniques. These methods generally require each source excitation to be solved for one at a time. Consequently, a 2.5D inversion may take hours to days on a standard serial computer, while the 3D inversion can only be tractable using massively parallel resources.
In the present application, a fast rigorous 2.5D forward and inversion algorithms for the interpretation of marine CSEM data is described. The forward scheme provides for simultaneous solution of all source-receiver configurations in a matter of minutes rather than hours. This in turn allows for rapid inversion algorithms.